SoroushVahidi/scidocs huggingface dataset:
New Support Vector Algorithms
(2000)

We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter in the regression case, and the regularization constant C in the classification case. We describe the algorithms, give some theoretical results concerning the meaning and the choice of , and report experimental results.
RNN-based sequence prediction as an alternative or complement to traditional recommender systems
(2017)

The recurrent neural networks have the ability to grasp the temporal patterns within the data. This is a property that can be used in order to help a recommender system better taking into account the user past history. Still the dimensionality problem that raises within the recommender system field also raises here as the number of items the system have to be aware of is susceptibility high. Recent research have studied the use of such neural networks at a user’s session level. This thesis rather examines the use of this technique at a whole user’s past history level associated with techniques such as embeddings and softmax sampling in order to accommodate with the high dimensionality. The proposed method results in a sequence prediction model that can be used as is for the recommender task or as a feature within a more complex system.
Developing multiple hypotheses in behavioral ecology
(2010)

Researchers in behavioral ecology are increasingly turning to research methods that allow the simultaneous evaluation of hypotheses. This approach has great potential to increase our scientific understanding, but researchers interested in the approach should be aware of its long and somewhat contentious history. Also, prior to implementing multiple hypothesis evaluation, researchers should be aware of the importance of clearly specifying a priori hypotheses. This is one of the more difficult aspects of research based on multiple hypothesis evaluation, and we outline and provide examples of three approaches for doing so. Finally, multiple hypothesis evaluation has some limitations important to behavioral ecologists; we discuss two practical issues behavioral ecologists are likely to face.
The Sixth PASCAL Recognizing Textual Entailment Challenge
(2009)

This paper presents the Fifth Recognizing Textual Entailment Challenge (RTE5). Following the positive experience of the last campaign, RTE-5 has been proposed for the second time as a track at the Text Analysis Conference (TAC). The structure of the RTE-5 Main Task remained unchanged, offering both the traditional two-way task and the threeway task introduced in the previous campaign. Moreover, a pilot Search Task was set up, consisting of finding all the sentences in a set of documents that entail a given hypothesis. 21 teams participated in the campaign, among which 20 in the Main Task (for a total of 54 runs) and 8 in the Pilot Task (for a total of 20 runs). Another important innovation introduced in this campaign was mandatory ablation tests that participants had to perform for all major knowledge resources employed by their systems.
Mindfulness-Based Cognitive Therapy and the Adult ADHD Brain: A Neuropsychotherapeutic Perspective
(2016)

Attention-deficit/hyperactivity disorder (ADHD) is a recognized serious mental disorder that often persists into adulthood. The symptoms and impairments associated with ADHD often cause significant mental suffering in affected individuals. ADHD has been associated with abnormal neuronal activity in various neuronal circuits, such as the dorsofrontostriatal, orbitofrontostriatal, and frontocerebellar circuits. Psychopharmacological treatment with methylphenidate hydrochloride is recommended as the first-line treatment for ADHD. It is assumed that medication ameliorates ADHD symptoms by improving the functioning of the brain areas affected in the condition. However, side effects, contraindications, or non-response can limit the effectiveness of a psychopharmacological treatment for ADHD. It is therefore necessary to develop non-pharmacological interventions that target neuronal mechanisms associated with the condition in the same way as pharmacological treatment. We think that mindfulness meditation employed as a neuropsychotherapeutic intervention could help patients with ADHD to regulate impaired brain functioning and thereby reduce ADHD symptoms. In this paper, we highlight the mechanisms of such mindfulness meditation, and thus provide a rationale for further research and treatment development from a neuropsychotherapeutic perspective. We conclude that mindfulness meditation employed as a neuropsychotherapeutic intervention in therapy is a promising treatment approach in ADHD.
Image-based reconstruction of wire art
(2017)

Objects created by connecting and bending wires are common in furniture design, metal sculpting, wire jewelry, etc. Reconstructing such objects with traditional depth and image based methods is extremely difficult due to their unique characteristics such as lack of features, thin elements, and severe self-occlusions. We present a novel image-based method that reconstructs a set of continuous 3D wires used to create such an object, where each wire is composed of an ordered set of 3D curve segments. Our method exploits two main observations: simplicity - wire objects are often created using only a small number of wires, and smoothness - each wire is primarily smoothly bent with sharp features appearing only at joints or isolated points. In light of these observations, we tackle the challenging image correspondence problem across featureless wires by first generating multiple candidate 3D curve segments and then solving a global selection problem that balances between image and smoothness cues to identify the correct 3D curves. Next, we recover a decomposition of such curves into a set of distinct and continuous wires by formulating a multiple traveling salesman problem, which finds smooth paths, i.e., wires, connecting the curves. We demonstrate our method on a wide set of real examples with varying complexity and present high-fidelity results using only 3 images for each object. We provide the source code and data for our work in the project website.
On the Semantics of Self-Unpacking Malware Code ∗
(2008)

The rapid increase in attacks on software systems via malware such as viruses, worms, trojans, etc., has made it imperative to develop effective techniques for detecting and analyzing malware binaries. Such binaries are usually transmitted in packed or encrypted form, with the executable payload decrypted dynamically and then executed. In order to reason formally about their execution behavior, therefore, we need semantic descriptions that can capture this self-modifying aspect of their code. However, current approaches to the semantics of programs usually assume that the program code is immutable, which makes them inapplicable to self-unpacking malware code. This paper takes a step towards addressing this problem by describing a formal semantics for self-modifying code. We use our semantics to show how the execution of self-unpacking code can be divided naturally into a sequence of phases, and uses this to show how the behavior of a program can be characterized statically in terms of a program evolution graph. We discuss several applications of our work, including static unpacking and deobfuscation of encrypted malware and static cross-phase code analysis.
An Information Retrieval Approach For Automatically Constructing Software Libraries
(1991)

Although software reuse presents clear advantages for programmer productivit.y and code reliability, it is not practiced enough. One of the reasons for the only moderate success of reuse is the lack of software libr'lries that facilitate the actual locating and understanding of reusable components. This paper dpscrihes II technology for automatically I\Ssembling large softwar~ libraries that promote softwarp rpuse by helping the user locate the components closest to hfO'r/his neeels Softwarp libraries are aut.omatically assemblfO'd from a set. of Ilnorganizpd component.s by using informat.ion rptripval techniques. The constrllction of the library is done in !.wo steps. First, attribut.es ;up alJtornal.ically pxtracted from nat.urlll language docllmpntat.ion by IIsing a npIV inJexing scheme ba~fO'd an t.he nntinns of lexical affinities anci quantity of inforrnllt.ion. Then, a hierarchy for browsing is alJtomat.iclllly generaterl using a clustering techniq1le that draws only nn the informlltion provided by the attribulps. Thanks to the frfO'p-!.pxt inrlexing se-heme, tools following this approach can accept free-style nat'Jral language 'luprips. This tpChllOlogy h1\.S bfO'en impll"ment .. d in the GURU ~ystpm, whirh h<l5 bpen applied 1.0 construct an organized library of Alx utilities. An exppriment. was rondllrtpd in orrlpr to pvalullte the n·t.rievll\ effectivl"nfO'ss of GURU 1\.5 compl\red to INFOExPLORER a hypprt.pxt lihrary syslplll for Alx 3 on the IBM RISe System/6000 series. We followpr\ Ihe usual evaluation prOf"pr\lJr!' us .. .! in informat.ion rptrifO'vl\l, hased upon recall and precision ml"a5IJrPS, and d"t.erminpd t 1111 I. nllr syst.f'Tll pr>rforms l!i% better on a random test set, while being milch le~s pxpensive to build than INFOEXl'LORF.R.
NOSEP: Nonoverlapping Sequence Pattern Mining With Gap Constraints
(2018)

Sequence pattern mining aims to discover frequent subsequences as patterns in a single sequence or a sequence database. By combining gap constraints (or flexible wildcards), users can specify special characteristics of the patterns and discover meaningful subsequences suitable for their own application domains, such as finding gene transcription sites from DNA sequences or discovering patterns for time series data classification. Due to the inherent complexity of sequence patterns, including the exponential candidate space with respect to pattern letters and gap constraints, to date, existing sequence pattern mining methods are either incomplete or do not support the Apriori property because the support ratio of a pattern may be greater than that of its subpatterns. Most importantly, patterns discovered by these methods are either too restrictive or too general and cannot represent underlying meaningful knowledge in the sequences. In this paper, we focus on a nonoverlapping sequence pattern mining task with gap constraints, where a nonoverlapping sequence pattern allows sequence letters to be flexibly and maximally utilized for pattern discovery. A new Apriori-based nonoverlapping sequence pattern mining algorithm, NOSEP, is proposed. NOSEP is a complete pattern mining algorithm, which uses a specially designed data structure, Nettree, to calculate the exact occurrence of a pattern in the sequence. Experimental results and comparisons on biology DNA sequences, time series data, and Gazelle datasets demonstrate the efficiency of the proposed algorithm and the uniqueness of nonoverlapping sequence patterns compared to other methods.
A CMOS Transceiver for a Multistandard 13.56-MHz RFID Reader SoC
(2010)

A CMOS transceiver for a multistandard 13.56-MHz radio-frequency identification reader system-on-a-chip (SoC) is designed and fabricated. The SoC consists of an RF/analog part for modulation/demodulation and a digital part for controlling the transceiver functionality. Prior to designing the integrated circuit, pre-experiments using discrete components and commercial tags are performed. With the results, overall functions and specifications are determined. For supporting multistandard, several blocks are designed with digital controls according to the standards. In the transmitter, a digitally controlled amplitude modulator for various modulation indexes and a power control circuit are adopted. In the receiver, a variable gain amplifier and a level-controllable comparator, which are also controlled digitally according to the standard, are introduced. The full transceiver SoC is implemented in the Chartered 0.18-¿m CMOS technology. The measurement results of the implemented chip indicate that the designed transceiver operates in a multistandard mode.
The contagious leader: impact of the leader's mood on the mood of group members, group affective tone, and group processes.
(2005)

The present study examined the effects of leaders' mood on (a) the mood of individual group members, (b) the affective tone of groups, and (c) 3 group processes: coordination, effort expenditure, and task strategy. On the basis of a mood contagion model, the authors found that when leaders were in a positive mood, in comparison to a negative mood, (a) individual group members experienced more positive and less negative mood, and (b) groups had a more positive and a less negative affective tone. The authors also found that groups with leaders in a positive mood exhibited more coordination and expended less effort than did groups with leaders in a negative mood. Applied implications of the results are discussed.
A 3-Month, Randomized, Double-Blind, Placebo-Controlled Study Evaluating the Ability of an Extra-Strength Marine Protein Supplement to Promote Hair Growth and Decrease Shedding in Women with Self-Perceived Thinning Hair
(2015)

An oral marine protein supplement (MPS) is designed to promote hair growth in women with temporary thinning hair (Viviscal Extra Strength; Lifes2good, Inc., Chicago, IL). This double-blind, placebo-controlled study assessed the ability of MPS to promote terminal hair growth in adult women with self-perceived thinning hair associated with poor diet, stress, hormonal influences, or abnormal menstrual cycles. Adult women with thinning hair were randomized to receive MPS (N = 30) or placebo (N = 30) twice daily for 90 days. Digital images were obtained from a 4 cm(2) area scalp target area. Each subject's hair was washed and shed hairs were collected and counted. After 90 days, these measures were repeated and subjects completed Quality of Life and Self-Assessment Questionnaires. MPS-treated subjects achieved a significant increase in the number of terminal hairs within the target area (P < 0.0001) which was significantly greater than placebo (P < 0.0001). MPS use also resulted in significantly less hair shedding (P = 0.002) and higher total Self-Assessment (P = 0.006) and Quality of Life Questionnaires scores (P = 0.035). There were no reported adverse events. MPS promotes hair growth and decreases hair loss in women suffering from temporary thinning hair. This trial is registered with ClinicalTrials.gov Identifier: NCT02297360.
Digital Advertising: An Information Scientist's Perspective
(2011)

Digital online advertising is a form of promotion that uses the Internet and World Wide Web for the express purpose of delivering marketing messages to attract customers. Examples of online advertising include text ads that appear on search engine results pages, banner ads, in-text ads, or Rich Media ads that appear on regular web pages, portals, or applications. Over the past 15 years online advertising, a $65 billion industry worldwide in 2009, has been pivotal to the success of the World Wide Web. That being said, the field of advertising has been equally revolutionized by the Internet, World Wide Web, and more recently, by the emergence of the social web, and mobile devices. This success has arisen largely from the transformation of the advertising industry from a low-tech, human intensive, “Mad Men” way of doing work to highly optimized, quantitative, mathematical, computerand data-centric processes that enable highly targeted, personalized, performance based advertising. This chapter provides a clear and detailed overview of the technologies and business models that are transforming the field of online advertising primarily from statistical machine learning and information science perspectives.
Design on the low-leakage diode string for using in the power-rail ESD clamp circuits in a 0.35-/spl mu/m silicide CMOS process
(2000)

A new design of the diode string with very low leakage current is proposed for use in the ESD clamp circuits across the power rails. By adding an NMOS-controlled lateral SCR (NCLSCR) device into the stacked diode string, the leakage current of this new diode string with six stacked diodes at 5 V (3.3 V) forward bias can be reduced to only 2.1 (1.07) nA at a temperature of 125/spl deg/C in a 0.35 /spl mu/m silicide CMOS process, whereas the previous designs have a leakage current in the order of mA. The total blocking voltage of this new design with NCLSCR can be linearly adjusted by changing the number of the stacked diodes in the diode string without causing latch-up danger across the power rails. From the experimental results, the human-body-model ESD level of the ESD clamp circuit with the proposed low-leakage diode string is greater than 8 kV in a 0.35 /spl mu/m silicide CMOS process by using neither ESD implantation nor the silicide-blocking process modifications.
Zero-bias autoencoders and the benefits of co-adapting features
(2014)

Regularized training of an autoencoder typically results in hidden unit biases that take on large negative values. We show that negative biases are a natural result of using a hidden layer whose responsibility is to both represent the input data and act as a selection mechanism that ensures sparsity of the representation. We then show that negative biases impede the learning of data distributions whose intrinsic dimensionality is high. We also propose a new activation function that decouples the two roles of the hidden layer and that allows us to learn representations on data with very high intrinsic dimensionality, where standard autoencoders typically fail. Since the decoupled activation function acts like an implicit regularizer, the model can be trained by minimizing the reconstruction error of training data, without requiring any additional regularization.
Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis.
(2014)

PURPOSE
Glaucoma is the leading cause of global irreversible blindness. Present estimates of global glaucoma prevalence are not up-to-date and focused mainly on European ancestry populations. We systematically examined the global prevalence of primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG), and projected the number of affected people in 2020 and 2040.


DESIGN
Systematic review and meta-analysis.


PARTICIPANTS
Data from 50 population-based studies (3770 POAG cases among 140,496 examined individuals and 786 PACG cases among 112 398 examined individuals).


METHODS
We searched PubMed, Medline, and Web of Science for population-based studies of glaucoma prevalence published up to March 25, 2013. Hierarchical Bayesian approach was used to estimate the pooled glaucoma prevalence of the population aged 40-80 years along with 95% credible intervals (CrIs). Projections of glaucoma were estimated based on the United Nations World Population Prospects. Bayesian meta-regression models were performed to assess the association between the prevalence of POAG and the relevant factors.


MAIN OUTCOME MEASURES
Prevalence and projection numbers of glaucoma cases.


RESULTS
The global prevalence of glaucoma for population aged 40-80 years is 3.54% (95% CrI, 2.09-5.82). The prevalence of POAG is highest in Africa (4.20%; 95% CrI, 2.08-7.35), and the prevalence of PACG is highest in Asia (1.09%; 95% CrI, 0.43-2.32). In 2013, the number of people (aged 40-80 years) with glaucoma worldwide was estimated to be 64.3 million, increasing to 76.0 million in 2020 and 111.8 million in 2040. In the Bayesian meta-regression model, men were more likely to have POAG than women (odds ratio [OR], 1.36; 95% CrI, 1.23-1.52), and after adjusting for age, gender, habitation type, response rate, and year of study, people of African ancestry were more likely to have POAG than people of European ancestry (OR, 2.80; 95% CrI, 1.83-4.06), and people living in urban areas were more likely to have POAG than those in rural areas (OR, 1.58; 95% CrI, 1.19-2.04).


CONCLUSIONS
The number of people with glaucoma worldwide will increase to 111.8 million in 2040, disproportionally affecting people residing in Asia and Africa. These estimates are important in guiding the designs of glaucoma screening, treatment, and related public health strategies.
Fuzzy Logic Based-Map Matching Algorithm for Vehicle Navigation System in Urban Canyons
(2004)

With the rapid progress in the development of wireless technology, Global Positioning System (GPS) based vehicle navigation systems are being widely deployed in automobiles to serve the location-based needs of users and for efficient traffic management. An essential process in vehicle navigation is to map match the position obtained from GPS (or/and other sensors) on a road network map. This process of map matching in turn helps in mitigating errors from navigation solution. GPS based vehicle navigation systems have difficulties in tracking vehicles in urban canyons due to poor satellite availability. High Sensitivity GPS (HS GPS) receivers can alleviate this problem by acquiring and tracking weak signals (and increasing the availability), but at the cost of high measurement noise and errors due to multipath and cross correlation. Position and velocity results in such conditions are typically biased and have unknown distributions. Thus filtering and other statistical methods are difficult to implement. Soft computing has replaced classical computing on many fronts where uncertainties are difficult to model. Fuzzy logic, based on fuzzy reasoning concepts, is one of the most widely used soft computational methods. In many circumstances, it can take noisy, imprecise input, to yield crisp (i.e. numerically accurate) output. Fuzzy logic can be applied effectively to map match the output from a HS GPS receiver in urban canyons because of its inherent tolerance to imprecise inputs. This paper describes a map matching algorithm based on fuzzy logic. The input of the system comes from a SiRF HS XTrac GPS receiver and a low cost gyro (Murata ENV-05G). The results show an improvement in tracking the vehicle in urban canyon conditions.
Automatic design of low power CMOS buffer-chain circuit using differential evolutionary algorithm and particle swarm optimization
(2017)

PSO and DE algorithms and its variants are used for the optimization of a buffer-chain circuit and the results of all the algorithms are compared in this literature. By testing these algorithms on different mathematical benchmark functions the best parameter values of buffer chain circuit are obtained in such a way that it reduces the error between simulated output and optimized output, hence giving the best circuit performance. Evolutionary algorithms are better in performance and speed than the classical methods. 130nm CMOS technology has been used in this work. With the help of these parameter values the circuit simulator gives the values of power consumption, symmetry, rise time and fall time, which are almost closer to the desired specification of the buffer chain circuit.